“Sampling of GB300 systems began earlier this month at the major CSPs, and we expect production shipments to commence later this quarter.”

In context

“owest cost per inference token. These systems are complex to build, we have seen a significant improvement in manufacturing yields, and rack shipments are moving to strong rates to end customers. GB200 and VO racks are now generally available for model builders, enterprises, and sovereign customers to develop and deploy AI. On average, major hyperscalers are each deploying nearly 1,000 NBL72 racks, or 72,000 Blackwell GPUs per week, and are on track to further ramp output this quarter. Microsoft, for example, has already deployed tens of thousands of Blackwell GPUs and is expected to ramp to hundreds of thousands of GB200s with OpenAI as one of its key customers. Key learnings from the GB200 ramp will allow for a smooth transition to the next phase of our product roadmap, Blackwell Ultra. Sampling of GB300 systems began earlier this month at the major CSPs, and we expect production shipments to commence later this quarter. GB300 will leverage the same architecture, same physical footprint, and the same electrical and mechanical specifications as GB200. The GB300 drop-in design will allow CSPs to seamlessly transition their systems and manufacturing used for GB200 while maintaining high yields. B300 GPUs, with 50% more HBM, will deliver another 50% increase in dense FP4 inference compute performance compared to the B200. We remain committed to our annual product cadence with our roadmap extending through 2028, tightly aligned with the multiple-year planning cycles of our customers. We are witnessing a sharp jump in inference demand. OpenAI, Microsoft, and Google are seeing a step function leap in token generation. Microsoft processed over 100 trillion tokens in Q1, a fivefold increase on a year-over-year bas”